Knowledge Reused Outlier Detection

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

FP-outlier: Frequent pattern based outlier detection

An outlier in a dataset is an observation or a point that is considerably dissimilar to or inconsistent with the remainder of the data. Detection of such outliers is important for many applications and has recently attracted much attention in the data mining research community. In this paper, we present a new method to detect outliers by discovering frequent patterns (or frequent itemsets) from...

متن کامل

Outlier Detection by Boosting Regression Trees

A procedure for detecting outliers in regression problems is proposed. It is based on information provided by boosting regression trees. The key idea is to select the most frequently resampled observation along the boosting iterations and reiterate after removing it. The selection criterion is based on Tchebychev’s inequality applied to the maximum over the boosting iterations of ...

متن کامل

Cross-Outlier Detection

The problem of outlier detection has been studied in the context of several domains and has received attention from the database research community. To the best of our knowledge, work up to date focuses exclusively on the problem as follows [1]: “given a single set of observations in some space, find those that deviate so as to arouse suspicion that they were generated by a different mechanism....

متن کامل

Rank-Based Outlier Detection

We propose a new approach for outlier detection, based on a new ranking measure that focuses on the question of whether a point is “important” for its nearest neighbors; using our notations low cumulative rank implies the point is central. For instance, a point centrally located in a cluster has relatively low cumulative sum of ranks because it is among the nearest neighbors of its own nearest ...

متن کامل

Automatic Group-Outlier Detection

We propose in this paper a new measure called GOF (Group Outlier Factor) to detect groups outliers. To validate this measure we integrated it in a clustering process using Self-organizing Map. The proposed approach is based on relative density of each group of data and simultaneously provides a partitioning of data and a quantitative indicator (GOF). The obtained results are very encouraging to...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Access

سال: 2019

ISSN: 2169-3536

DOI: 10.1109/access.2019.2906644